A Valorized Scheme for Failure Prediction Using ANFIS: Application to Train Track Breaking System

• 作者: Bertin Sohfotsing Olivier Garro Tibi Beda Tse Sparthan Wolfgang Nzie
• 来源期刊: 应用科学(英文)
• 学科: 经济
• 关键词: Failure Prediction (FP) Remaining Useful Life (RUL) Artificial Intelligence (AI) Traintrack System ANFIS Modeling
• 年，卷（期）: 2020,（11）
• 页码范围: 732-757
• 页数: 26页
• 分类号: F42

摘要

In the rolling stock sector, the ability to protect passengers, freight and services relies on heavy inborn maintenance. Initiating an accurate model suitable to foresee the change of attitude on components when operating rolling stock systems will assist in reducing lock down and favors heavy productivity. In that light, this paper showcases a suitable methodology to track degradation of components through the blinding of physic laws and artificial intelligent techniques. This model used to foresee failure deterioration rate and remaining useful life (RUL) speculation is case study to showcase its quality and perfection, within which behavioral data are obtained through simulated models initiated in Mathlab. For feature extraction and forecasting issues, different neuro-fuzzy inference systems are designed, learnt and authenticated with powerful outputs gained during this process.